A numerical study of 3D droplets of active matter reveals many dynamical responses to a microscopic influx of energy, such as fingerlike protrusions and surface wrinkling, offering new physics insight into life sciences.

Predicting effective characteristics of electromagnetic waves in composite media is an old problem with limited solutions. A new theoretical framework overcomes those limitations.

A new method for analyzing summaries of network structure given by clustering algorithms provides a way to characterize competing solutions and extract more meaningful results.

The Green function is a crucial description of a system’s response to an impulse but is challenging to measure experimentally. A new measurement technique fully characterizes the function for a resonant planar cavity.

By identifying how fractional electron filling manifests in effective field theory, a new analysis offers a more general way to understand certain collective behaviors of electrons in a solid.

A new framework for “quantum embedding methods,” which enable tractable predictions of correlated electron materials, improves accuracy by avoiding approximations used by previous approaches.

A surprisingly large suppression of laser light in confocal microscopy studies of resonant fluorescence has its origins in a small shift of polarized light reflecting off smooth surfaces.

The commonly expected infinite-temperature-like state in a periodically driven homogeneous system of interacting particles can be avoided if the system is quantum mechanical and the drive is strong enough.

A silicon carbide nanowire suspended in an optical microcavity serves to map the strength and orientation of the optomechanical interaction, down to the single-photon level.

A quantum processor based on three-level “qutrits,” as opposed to two-level qubits, successfully runs a quantum teleportation algorithm in a proof-of-concept demonstration of resource-efficient three-level systems.

Bubbles in helium droplets form around excited atoms and greatly accelerate interatomic Coulombic decay, showing how environment enhances this biologically relevant energy-sharing process among atoms and molecules.

An all-electrical technique resolves the dispersion relation of spin waves in bilayer graphene, shedding light on the magnetic order of a quantum Hall canted antiferromagnet.

Universal bounds on dissipation offer a powerful new tool to measure and optimize the performance of thermal quantum devices.

No matter how clever the design of a quantum computer, the laws of physics demand a minimum amount of energy to produce accurate computations.

Adsorption of hydrogen onto a ferromagnetic surface induces and controls a winding arrangement of magnetic moments potentially useful in future energy-efficient information applications.

Observations of an ideal magnetic topological state in the ferromagnet EuB${}_6$ offer the promise of realizing novel electronic and magnetic states in 2D materials.

A numerical investigation of flow behavior in a cohesive granular material reveals complex dynamics that may help improve industrial applications that rely on powders.

A voltage-controlled transition from a non-Fermi-liquid state in a metal to a typical Fermi-liquid state precedes the onset of ferromagnetism, new experiments show.

A new framework for analyzing resources in quantum information processing shows how quantum superposition offers a novel advantage in memory usage compared with classical devices.

A new platform based on a hybrid optomechanical microcavity for coupling of electrically excited gigahertz phonons and exciton-polaritons provides a coherent interface between microwave and near-infrared photons.

A correspondence principle between classical periodic orbits and quantum states of Rydberg atom chains sheds light on “quantum many-body scarring,” in which these chains repeatedly revisit their initial states.

Using an optical lattice of cold atoms, quantum simulation of a single electron hole added to an antiferromagnet reveals how the hole alters the spin environment and how the spins slow down the hole.

Terahertz spectroscopy reveals the microscopic dynamics underlying soft vibrational modes in a ferroelectric material, providing inroads to all-optical control of nonlinear functional materials.

The moiré pattern formed on the surface of a topological insulator could lead to enhanced topological superconductivity.

The disassembly of a virus’ protein shell must happen at the right time to ensure transfer of the viral genome to its host. New experiments reveal that aging determines the dynamics of this unraveling.

A high-fidelity quantum logic gate implemented with fluxonium-based qubits offers a new route to scalable and robust quantum processors.

Optical spectroscopy provides direct evidence of electrons organizing themselves into a periodic distribution in the correlated insulating state of a twisted bilayer 2D semiconductor.

A theoretical and numerical study stresses the importance of higher-order moments of density fluctuations in characterizing models of many-body systems.

An experiment with a nanoscale clock verifies that a clock’s entropy per tick increases as the clock is made more precise.

In magnetic metals, electrical resistance depends on the direction of magnetization relative to the current. New experiments show that this effect does not depend solely on electron collisions, as is typically assumed.

Researchers have created subradiant states—in which collective effects prevent excited atoms from decaying—in a dense atomic cloud.

A new theoretical framework connects the fluctuations in gene expression with fundamental cell dynamics including cellular division and DNA replication.

Randomly distributed atomic-level defects in the magnetic topological insulator MnSb${}_2$Te${}_4$ help stabilize ferromagnetic interactions but are detrimental to topological electronic properties.

By tuning interatomic interactions among cold atoms, new experimental work demonstrates a device in which the magnitude and direction of a thermoelectric current can be controlled.

A new algorithm for solving a large 2D grid of interacting particles provides much more accurate predictions of how such systems interact with their environment than previous techniques.

A method that enables long-range interactions between fermions on a lattice allows atomic quantum simulations of exotic quantum many-body phenomena.

A generalization of fundamental symmetry classes of fermionic quantum matter to out-of-equilibrium systems provides a framework for engineering novel quantum phases.

Resistive anisotropy grows then shrinks following the onset of electronic nematicity in FeSe, a key observation of how the electronic structure of FeSe changes as nematicity develops.

A new method to compute physical properties of interacting many-body quantum systems can do so exponentially faster than other techniques.

A new theoretical framework provides a way to predict nonequilibrium dynamics in quantum-many body systems.

Time lag in how an environment responds to a quantum device complicates analyses of these systems, but an elegant workaround provides a way to proceed as if there were no lag at all.

A mathematical analysis shows how changes in the brightness and polarization of light emitted by excitons in a transition-metal dichalcogenide bilayer is a powerful probe of exciton behavior.

Quantum inflation offers the mathematical tools to identify and quantify causal relationships among quantum systems with ready applications to entanglement theory and quantum information protocols.

Neutron-scattering experiments provide solid evidence for the elusive quantum spin liquid state in a 2D triangular crystalline material.

A proposed approach could allow physical networks to learn how to adapt to stimuli and gain desired functionalities, exporting a machine-learning methodology to real materials and machines.

Quantum machine-learning techniques speed up the task of classifying data delivered by a small network of quantum sensors.

Merging ideas from neuroscience, machine learning, and quantum technology, researchers propose a new information-storage device.

Laser ion acceleration driven by the utmost intense laser pulses pushes superheavy gold ions to unprecedented energies, key for applications ranging from nuclear physics to next-generation accelerators.

Theorists have shown that carefully patterned surfaces can transform the emission from a hot object into a polarized, focused light beam.

A new framework for analyzing chaotic quantum systems with local interactions identifies generic many-body interference effects, with strong implications for quantum spectra.

A neural network maps arbitrary nanostructure patterns to their wave band structures and finds geometries that support desired wave propagation behavior, a key advance in tailoring wave transport in nanodevices.

An updated catalog of gravitational-wave detections includes 50 events consistent with a wide range of mergers among compact astrophysical objects.

A monolayer of FeSe atop SrTiO${}_3$ displays enhanced high-temperature superconductivity. New measurements reveal a sharp distinction between the appearance of a superconducting energy gap and true zero resistivity.

A demonstration of high-quality electron beams from a plasma accelerator driven by a low-energy, few-cycle duration laser pulse showcases a promising low-cost alternative to large traditional accelerators.

A method for visualizing rotation of micrometer-sized spheres reveals for the first time how hydrodynamic and frictional effects affect rotational motion in particulate suspensions.

A novel thermodynamic framework extends the notion of heat to active materials as a tool to quantify the energetic cost of sustaining nonequilibrium patterns in these active systems.

Two-qubit gate errors remain a major bottleneck on the road to robust quantum computing. A new approach to designing a key element of such gates dramatically improves their fidelity.

External input introduced to a spreading cascade in a network fundamentally alters the growth of that cascade—a new insight with implications for understanding brain dynamics.

A machine-learning approach quickly characterizes an optical fiber, identifying transmission channels that aren’t affected by deformation.

Particle number nonconservation in interactions among magnons in ferromagnet models reveal a topological phase transition, which opens possibilities for energy-efficient magnetic information processing.

A synergy between strongly electron-correlated physics, quantum transport theory, and quantum information science provides a long-sought quantum-mechanical description of spin torque, an effect at the heart of spintronic research.

Two distinct classes of turbulence are studied through the lens of statistical physics, but a certain kind of discrete model bridges these classes and can describe both.

A framework for comparing models of neural networks provides insight into how the brain can support powerful computations despite its strongly chaotic electrical activity.

A newly discovered 3D topological Dirac semimetal exhibits surface superconductivity at ambient pressure, a key step in the development of systems sought after for quantum computation.

Bacteria-infecting viruses provide a controllable platform to study the expansion of a virus in a cell population.

A theoretical and computational analysis shows that it is possible to precisely control the optical properties of a material by optically exciting crystalline lattice vibrations, or phonons.